rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Passivity-Based Model Predictive Control for Mobile Vehicle Motion Planning
  name:
    name part: Tahirovic, Adnan.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Magnani, Gianantonio.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxk
    date issued: 2013
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XI, 56 p. 20 illus., 17 illus. in color. online resource.
  abstract: Passivity-based Model Predictive Control for Mobile Vehicle Navigation represents a complete theoretical approach to the adoption of passivity-based model predictive control (MPC) for autonomous vehicle navigation in both indoor and outdoor environments. The brief also introduces analysis of the worst-case scenario that might occur during the task execution. Some of the questions answered in the text include: • how to use an MPC optimization framework for the mobile vehicle navigation approach; • how to guarantee safe task completion even in complex environments including obstacle avoidance and sideslip and rollover avoidance; and • what to expect in the worst-case scenario in which the roughness of the terrain leads the algorithm to generate the longest possible path to the goal. The passivity-based MPC approach provides a framework in which a wide range of complex vehicles can be accommodated to obtain a safer and more realizable tool during the path-planning stage. During task execution, the optimization step is continuously repeated to take into account new local sensor measurements. These ongoing changes make the path generated rather robust in comparison with techniques that fix the entire path prior to task execution. In addition to researchers working in MPC, engineers interested in vehicle path planning for a number of purposes: rescued mission in hazardous environments; humanitarian demining; agriculture; and even planetary exploration, will find this SpringerBrief to be instructive and helpful.
  table of contents: Introduction -- PB/MPC Navigation Planner -- PB/MPC-RT Planner For Rough Terrains -- Conclusion.
  note: by Adnan Tahirovic, Gianantonio Magnani.
  subject:
    topic: Engineering
  subject:
    topic: Automotive engineering
  subject:
    topic: Aerospace engineering
  subject:
    topic: Astronautics
  subject:
    topic: Control engineering
  subject:
    topic: Robotics
  subject:
    topic: Automation
  subject:
    topic: Engineering
  subject:
    topic: Control
  subject:
    topic: Robotics and Automation
  subject:
    topic: Automotive Engineering
  subject:
    topic: Aerospace Technology and Astronautics
  classification: TJ212-225
  classification: 629.8
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: SpringerBriefs in Electrical and Computer Engineering
  identifier: 9781447150497
  identifier: http://dx.doi.org/10.1007/978-1-4471-5049-7
  record info:
    record creation date: 130419
    record change date: 20151030051333.0
    record identifier: 978-1-4471-5049-7